|Publication number||US7411393 B2|
|Application number||US 11/336,376|
|Publication date||Aug 12, 2008|
|Filing date||Jan 20, 2006|
|Priority date||Nov 30, 2005|
|Also published as||EP1958153A2, US20070124117, WO2007064303A2, WO2007064303A3|
|Publication number||11336376, 336376, US 7411393 B2, US 7411393B2, US-B2-7411393, US7411393 B2, US7411393B2|
|Original Assignee||Bracco Imaging S.P.A.|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (26), Non-Patent Citations (8), Referenced by (11), Classifications (7), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
The present application claims priority to the United States provisional application entitled Method and System for Fiber Tracking, filed on Nov. 30, 2005, assigned application number 60/741,356, which is incorporated in its entirety herein.
Diffusion Tensor Imaging (DTI) visualization is a growing field of research. The scanners are collecting better data all the time, and doctors and scientists are constantly discovering new applications for the data. The success of diffusion magnetic resonance imaging (MRI) is rooted in the powerful concept that during their random, diffusion-driven displacements, molecules probe tissue structure at a microscopic scale well beyond the usual image resolution. As diffusion is a three dimensional process, molecular mobility in tissues may be anisotropic, as in brain white matter.
The diffusion anisotropy effects can be extracted, characterized, and exploited, providing details on tissue microstructure. One such advanced application is that of fiber tracking in the brain, which may provide insight into the issue of connectivity. DTI has also been used to demonstrate subtle abnormalities in a variety of diseases (including stroke, multiple sclerosis, dyslexia, and schizophrenia) and is currently becoming part of many routine clinical protocols.
However, there exist a need for a more intuitive input interface to let the user specify the tracts of interest, so as to make them part of the surgical planning and subsequent navigation.
One embodiment of the present invention includes a system comprising to determine a direction of tracking a fiber based on a vector corresponding to a largest value of a set of values for a tensor, if an anisotropy value of the tensor is greater than or equal to a first threshold; and to apply a weighted function to the vector of the tensor to select the direction of tracking the fiber, if the anisotropy value of the tensor is less than or equal to the first threshold and larger than or equal to a second threshold. In one embodiment, the system is to generate the weighted function comprises a linear interpolation to be performed on the vector. In one embodiment, a weight of the linear interpolation is in part dependent on the anisotropy value of the tensor, wherein the weight corresponds to the anisotropy value relative to the first threshold and the second threshold. One embodiment of the invention is also executable as a method.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.
One embodiment of the invention includes a DTI module interface comprising of one or more sub-modules, namely, “Compute Tensor”, “Visualization”, “Fiber Track” and “Fiber Management”. In alternative embodiments, a different set of sub-modules may be used. In one embodiment, the DTI module is operable with an input interface providing 3 degrees of spatial freedom to control input. The input interface, in effect, provides hand access inside a reference volume.
The compute tensor module is used to select the source DTI volume and the parameters with which to compute the tensors. The Visualization module provides a set of visualizations for the volumes, which may aid diagnosis. In an alternative embodiment, the source DTI volume can be loaded, the tensors automatically computed based on a predetermined set of parameters, and displayed via a predetermined visualization.
The Fiber Track module is used to track and visualize neuron fibers. In one embodiment, a ROI in the reference volume is specified as one or more 3D ROIs (e.g., a cube).
A Fiber Management module is also provided, in one embodiment, to organize fibers generated in the Fiber Track module. For example, the Fiber Management module allows the user to append, rename, or delete fibers. In one embodiment, a coloring tool is also supported to re-color the fibers and visually differentiate the various fibers.
As stated above, in one embodiment the DTI module is operable with an input interface providing at least 3 degrees of spatial freedom to control input (also referenced herein as the “input interface”). The input interface provides for 3D spatial interactive manipulations.
By way of illustration, to work with 3D rendered objects or reference volumes, the input interface includes one or more handheld instruments 102 a-b, such as a stylus. In one embodiment, the instruments allow the user to freely maneuver the instruments for 3 or more degrees of freedom. A corresponding image of a handheld instrument (also referenced herein as a “virtual tool”), along with its movements is displayed for interaction with a reference volume.
In one embodiment, maneuvering of a handheld device produces corresponding maneuvering of the displayed reference volume, which may be displayed as a 3D image. As a result, the reference can be rotated from different angles and moved in different directions. In one embodiment, a user activates the handheld device (e.g., presses a button on the handheld device 102 b) to have movement of the handheld device produce movement of the displayed reference volume, including maneuvering a position and orientation of the volume.
The movement of the handheld instruments, in one embodiment, is tracked by a radio frequency (rf) tracker. In an alternative embodiment, the input interface may comprise a haptic device for providing input control with the one or more handheld devices.
In alternative embodiments, more than two handheld devices may be provided. For example, multiple users may be able to interact with the reference volume, remotely or locally. In one embodiment, a single handheld device may be used to perform a set of the activities described above.
In one embodiment, a mirror 103 is placed between the user and the computer screen 106. The mirror reflects the reference volume and the virtual tool as displayed by the computer screen. The user's hands are able to move in a workspace 108 behind the mirror and interact with the reference volume shown by the reflection. As a result, the user is able to work with the reference volume with both hands without obscuring the reference volume. In addition, in one embodiment, the input interface is provided with a workstation 112 that includes a support 114 for the user's arm to rest.
In one embodiment, the reference volume may be displayed on the screen stereoscopically. In one embodiment, liquid crystal display (LCD) shutter glasses 120 are used to perceive the reference volume stereoscopically. The LCD shutter glasses allow light through in synchronization with the images on the computer display, using the concept of Alternate-frame sequencing. Multiple viewers may wear shutter glasses to simultaneously view and discuss the reference volume.
Complex applications like neurosurgery planning typically require frequent access to buttons and sliders that control applications and activate modes of operation and tools. As such, one embodiment includes a virtual tool panel to provide an integration of the workspace having at least 3 degrees of spatial freedom and application control.
In one embodiment, as illustrated in
In one embodiment, the input interface is operable with a process or module that is able to generate real-time volumetric and 3D spatial surface rendering of multimodal images based on one or more of computer tomography (CT), positron emission tomography (PET), single-photon emission computer tomography (SPECT), magnetic resonance imaging (MRI), magnetic resonance angiography imaging (MRA), volumetric ultrasound, and as well as segmentations obtained from one or more of the multimodal images. By using the input interface and the process together, in one embodiment a stereoscopic Virtual Reality (VR) environment is provided in which a user can work interactively in real-time with 3D data by “reaching into it” with both hands.
In one embodiment, the process comprises of one or more of the following features: perspective stereoscopic shaded volume and surface rendering; multimodality image fusion; automatic volume registration and verification of the registered objects; segmentation; surgical exploration tools for cropping, cutting, drilling, restoring, cloning, roaming, linear and volumetric measurement; color and/or transparency mapping with volume rendering preset; DICOM compliant, as well as supporting multiple file formats (e.g., TIFF); and capturing 3D spatial interactive manipulations, with stereoscopic playback and video export capabilities.
Diffusion Tensor Imaging (DTI) Module
As described above, in one embodiment, the DTI module comprises a set of sub-modules. They are the compute tensor module, visualization module, fiber track module and fiber management module. An alternative set of modules may be used without departing from the invention. For example, in one embodiment, the source DTI volume could be loaded and the tensors automatically computed based on a predetermined set of parameters, along with a predetermined visualization way pre-selected. In such an embodiment, the computation and/or the visualization modules may not be included in the DTI module for user interaction.
Compute Tensor Module
The object selector 204 of the panel 202 is provided to select the source DTI volume. In one embodiment, the number selector 206 in the panel is provided to specify the b value that is determined during the DWIs acquisition process. The b value parameter is used to compute tensors.
The slider 208 on the panel 202 is to specify the intensity threshold of the source DTI volume. In one embodiment, for those voxels with intensities smaller than the intensity threshold, the tensors (3*3 matrixes) are not computed and are considered as the zero matrixes. In this way, the tensors of the background voxels need not be computed, thereby increasing the speed of the tensor computation process.
When the compute tensor button 210 is pressed, the tensors for the source DTI volume are computed. In one embodiment, the features 212 provided on the panel 202 summarize the parameters used to compute the tensors. In one embodiment, the features 212 appear only after the tensors are computed. In alternative embodiments, the components provided on the panel 202 of the compute tensor module may vary without departing from the invention.
In one embodiment, DTI tensors of the source DTI volume are rendered by selecting visualization on the panel and then pressing the “Compute Volume” button 320 on the panel.
The FA, ADC, LA, PA, SA volumes are the grayscale volumes that show the diffusion property of the DTI tensors. In FA volume, the voxel with higher intensity indicates that the diffusion of the tensors in this voxel is more anisotropic, as illustrated by way of example in
In one embodiment, the FA color volume is the color-coded volume that shows the direction information of the tensors, as illustrated by way of example in
In one embodiment, the direction method generates and displays a set of lines indicating the largest diffusion directions of all the DTI tensors, as illustrated by way of example in
Fiber Track Module
In one embodiment, the computed tensors may be visualized as fiber tracks (also referenced herein as fiber bundles) via the Fiber Track Module. One embodiment allows a user to identify 2D and/or 3D region of interests (ROIs) on a reference volume, and compute the fibers passing through these ROIs. In one embodiment, the fiber tracking module is operable with the input interface providing at least 3 degrees of spatial freedom to control input, as described above. In one embodiment, as illustrated in
In one embodiment, as further illustrated in
In one embodiment, the fiber bundles that pass through an ROI are computed and displayed. Alternatively, the fibers for the entire volume may have already been generated but are not displayed, and therefore the fiber bundles that pass through a ROI are identified and displayed. Hence, as described herein, in one embodiment, reference to computing and/or generating fiber bundles or fiber tracks may include identifying and displaying the fiber bundles, computing and displaying the fiber bundles, or computing and not displaying the fiber bundles.
In one embodiment, as illustrated in
As further shown in
In one embodiment, the size of the 3D cube can be adjusted in real-time, and thereby changing the size of ROIs to be selected. The size of the 3D cube can be adjusted via an input control feature included on a control panel, or an input control feature included on a handheld device of the input interface.
In alternative embodiments, objects other than a 3D cube may be used without departing from the invention. For example, pre-set 3D regions of interest may be provided. The pre-set 3D ROIs could be defined and positioned by probabilistic methods. For example, co-registered DTI atlas information could be used to auto-detect a region which will likely contain a particular fiber track. The input interface and the DTI module, described herein, could then be used to modify the region in terms of size or shape of the pre-set 3D ROIs.
In one embodiment, as illustrated in
As shown in
In one embodiment, a user can also delete previously marked 3D ROIs identified with the 3D cubes placed in the reference volume. In one embodiment, a user may select the delete button 626 on the control panel 620 of the Fiber tracking module, as shown in
In one embodiment, regions within the reference volume can be identified to be avoided and not part of a ROI for generating fiber bundles. In one embodiment, an additional button can be provided in the 3D ROI interface (e.g., on the panel of the Fiber track module.) One or more cubes can be placed on the reference volume to identify a ROI that is to be avoided. In one embodiment, cubes corresponding to the ROIs to be avoided are of different color (or of different shape) relative to the cubes identifying the ROIs for generating the fiber bundles. When the user starts to compute the fibers, the fiber tracking algorithm will consider these avoid ROIs, and discard those fibers passing through the avoid ROIs.
In one embodiment, as illustrated in
In one embodiment, the reference volume used with the fiber tracking module may be a DTI volume, or a CT, PET, SPECT, MRI, MRA, volumetric ultrasound, or the other multimodality volumes co-registered with a DTI volume. In addition, in one embodiment, a segmented image, obtained from one or more of the multimodality volumes co-registered with the DTI volumes, can be used as a reference volume.
In one embodiment, the fiber tracking panel 620 further includes an interface to adjust the stop conditions for fiber tracking. In one embodiment, the stop conditions include one or more of: FA threshold, maximum length threshold, minimum length threshold, and the deviation angle threshold. By adjusting the above thresholds, a user can obtain the fibers with different shapes and lengths. The step length slider is used to control the smoothness of the fibers. For example, if the step length is smaller, the fibers may be shown smoother and more accurate. Using these controls, a user may then find the parameters that yield the desired fiber tracking results.
In process 1204, the eigenvector corresponding to the largest eigenvalue is identified for the tensors of the voxels in a ROI. Tracking of the respective fiber proceeds along the direction of this eigenvector.
In process 1206, tracking continues along the current tracking direction for a short distance and a new point is reached. In one embodiment, the short distance is referenced as the step length and can be a fixed value or an adaptive value. If the step length is fixed, then the step length is fixed to some value. In one embodiment, the user can adjust the value by adjusting the step length slider previously described. If the step length is adaptive, then the distance changes during the fiber tracking process according to an anisotropy value of the tensor on the previous point.
In process 1208, if the new point is out of bounds relative to the source DTI volume, the tracking is terminated 1210. In particular, in one embodiment, the reference volume has a bounding box that indicates the size of the source DTI volume. If the new point is outside of this bounding box, the tracking is out of bound and the tracking is terminated. Otherwise, in process 1212, a tri-linear interpolation process is used to compute a new tensor at the new point, and the eigenvectors and eigenvalues are computed for the new tensor.
In process 1214, if the Fractional Anisotropy (FAnew) value of the new tensor is less than the FA1 (i.e., a predefined threshold), the tracking is terminated 1210. In process 1216, if FAnew is between FA1 and FA2 (FA2 is a predefined thresholds with FA2>FA1), a separate process is used to generate the next candidate tracking direction. Otherwise, in process 1218 tracking of the respective fiber proceeds along the direction of the eigenvector corresponding to the largest eigenvalue for the new tensor. In alternative embodiments, measurements other than FA can be used without departing from the invention.
In process 1220, if a deviation angle between the current track direction and next candidate tracking direction is larger than a predefined threshold, the tracking is terminated 1210. Otherwise, in process 1222 the fiber tracking continues along the next tracking direction and the process continues again at process 1206. In one embodiment, the processes 1202-1222 are performed for a set of the voxels identified with an identified ROI. In alternative embodiments, some of the processes described can be excluded, as well as additional processes included, without departing from the scope of the invention.
In one embodiment, the weight (w) used for the linear interpolation is a function of FAnew wherein FAnew=f(w). In one embodiment, when FAnew is smaller, the weight (w) is also smaller and vice versa.
Furthermore, in one embodiment variations of the weight are moderated relative to variations in the FA value. In one embodiment, to moderate the variations of the weight, a second order parabola (f) is used, which is defined as (f)=a*w*w +b*w+c. The coefficients a, b, c, in one embodiment, are determined based on using predefined correspondences of the FA value and the weight. In alternative embodiments, variations of determining the weight for the interpolation may be used without departing from the scope of the invention.
It is clear that many modifications and variations of this embodiment may be made by one skilled in the art without departing from the spirit of the novel art of this disclosure.
The processes described above can be stored in a memory of a computer system as a set of instructions to be executed. In addition, the instructions to perform the processes described above could alternatively be stored on other forms of machine-readable media, including magnetic and optical disks. For example, the processes described could be stored on machine-readable media, such as magnetic disks or optical disks, which are accessible via a disk drive (or computer-readable medium drive). Further, the instructions can be downloaded into a computing device over a data network in a form of compiled and linked version.
Alternatively, the logic to perform the processes as discussed above could be implemented in additional computer and/or machine readable media, such as discrete hardware components as large-scale integrated circuits (LSI's), application-specific integrated circuits (ASIC's), firmware such as electrically erasable programmable read-only memory (EEPROM's); and electrical, optical, acoustical and other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.); etc.
It is clear that many modifications and variations of this embodiment may be made by one skilled in the art without departing from the spirit of the novel art of this disclosure.
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|U.S. Classification||324/307, 324/309|
|Cooperative Classification||G01R33/5608, G01R33/546, G01R33/56341|
|Apr 13, 2006||AS||Assignment|
Owner name: BRACCO IMAGING SPA, ITALY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ZHANG, WEI;REEL/FRAME:017747/0360
Effective date: 20060224
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